[U] Refactor bot

This commit is contained in:
Hykilpikonna
2022-05-07 23:41:20 -04:00
parent 0101de51b0
commit c37788c86a
2 changed files with 30 additions and 57 deletions
+3 -4
View File
@@ -39,12 +39,11 @@ def process_audio(message: Message):
downloader.download(file)
# Segment file
seg = Segmenter()
result = process(seg, [str(file.absolute())]).results[0]
result = segment(file)
# Null case
print(result.frames)
if len(result.frames) == 0:
print(result)
if len(result) == 0:
bot.send_message(message.chat_id, '分析失败, 大概是音量太小或者时长太短吧, 再试试w')
return
+27 -53
View File
@@ -14,14 +14,18 @@ import numpy as np
import scipy.io.wavfile
from PIL import Image
from inaSpeechSegmenter import *
from inaSpeechSegmenter.segmenter import featGenerator
from matplotlib.figure import Figure, Axes
from matplotlib.axes import Axes
from matplotlib.figure import Figure
seg = Segmenter()
class ResultFrame(NamedTuple):
gender: str
start: float
end: float
prob: float
class Result(NamedTuple):
@@ -29,37 +33,8 @@ class Result(NamedTuple):
file: str
class BatchResults(NamedTuple):
results: list[Result]
time_full: float
time_avg: float
successes: int
messages: list[tuple[str, int]]
def process(self: Segmenter, inp: list[str], tmpdir=None, verbose=False, skip_if_exist=False,
nbtry=1, try_delay=2.) -> BatchResults:
t_batch_start = time.time()
results: list[Result] = []
lmsg = []
fg = featGenerator(inp.copy(), inp.copy(), tmpdir, self.ffmpeg, skip_if_exist, nbtry, try_delay)
i = 0
for feats, msg in fg:
lmsg += msg
i += len(msg)
if verbose:
print('%d/%d' % (i, len(inp)), msg)
if feats is None:
break
mspec, loge, diff_len = feats
lseg = self.segment_feats(mspec, loge, diff_len, 0)
results.append(Result([ResultFrame(*s) for s in lseg], inp[len(lmsg) - 1]))
t_batch_dur = time.time() - t_batch_start
nb_processed = len([e for e in lmsg if e[1] == 0])
avg = t_batch_dur / nb_processed if nb_processed else -1
return BatchResults(results, t_batch_dur, avg, nb_processed, lmsg)
def segment(file) -> list[ResultFrame]:
return [ResultFrame(*s) for s in seg(file)]
def to_wav(file: str, callback: Callable, start_sec: float = 0, stop_sec: float = 0):
@@ -94,7 +69,7 @@ def show_image_buffer(buf):
buf.close()
def draw_result(file: str, result: Result):
def draw_result(file: str, result: list[ResultFrame]):
"""
Draw segmentation result
@@ -119,11 +94,11 @@ def draw_result(file: str, result: Result):
# Cutoff frequency so that the plot looks centered
cutoff = min(abs(min(audio)), abs(max(audio)))
ax.set_ylim([-cutoff, cutoff])
ax.set_xlim([result.frames[0].start, result.frames[-1].end])
ax.set_xlim([result[0].start, result[-1].end])
# Draw segmentation areas
colors = {'female': '#F5A9B8', 'male': '#5BCEFA', 'default': 'gray'}
for r in result.frames:
for r in result:
color = colors[r.gender] if r.gender in colors else colors['default']
ax.axvspan(r.start, r.end - 0.01, alpha=.5, color=color)
@@ -139,7 +114,7 @@ def draw_result(file: str, result: Result):
return to_wav(file, wav_callback)
def get_result_percentages(result: Result) -> tuple[float, float, float, float]:
def get_result_percentages(result: list[ResultFrame]) -> tuple[float, float, float, float]:
"""
Get percentages
@@ -148,8 +123,8 @@ def get_result_percentages(result: Result) -> tuple[float, float, float, float]:
"""
# Count total and categorical durations
total_dur = 0
durations: dict[str, int] = {f.gender: 0 for f in result.frames}
for f in result.frames:
durations: dict[str, int] = {f.gender: 0 for f in result}
for f in result:
dur = f.end - f.start
durations[f.gender] += dur
total_dur += dur
@@ -176,11 +151,10 @@ def test():
# [('../test.csv', 0)])
warnings.filterwarnings("ignore")
seg = Segmenter()
audio_file = '../test.flac'
# Warmup run
results = process(seg, [audio_file])
results = segment(audio_file)
print(results)
# # Actual run
@@ -188,18 +162,18 @@ def test():
# print(results)
# Benchmark
iterations = 60
total_time = 0
audio_len = float(subprocess.getoutput(f'ffprobe -i {audio_file} -show_entries format=duration -v quiet -of csv="p=0"'))
print(f'Audio length: {audio_len}')
for i in range(iterations):
results = process(seg, [audio_file])
total_time += results.time_full
time_per_second = total_time / iterations / audio_len
print(f'Benchmark result: {total_time}s / {iterations} iterations = {time_per_second} seconds of processing per second in audio')
print(f'Score: {1 / time_per_second}')
# iterations = 60
# total_time = 0
# audio_len = float(subprocess.getoutput(f'ffprobe -i {audio_file} -show_entries format=duration -v quiet -of csv="p=0"'))
# print(f'Audio length: {audio_len}')
#
# for i in range(iterations):
# results = process(seg, [audio_file])
# total_time += results.time_full
#
# time_per_second = total_time / iterations / audio_len
# print(f'Benchmark result: {total_time}s / {iterations} iterations = {time_per_second} seconds of processing per second in audio')
# print(f'Score: {1 / time_per_second}')
# Draw results
# with draw_result(audio_file, results.results[0]) as buf: